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margin-based transfer learning
Su Bai; Xu Wei; Shen Yidong
2009
会议名称6th International Symposium on Neural Networks
会议日期2009
会议地点Wuhan, PEOPLES R CHINA
出版地HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
出版者SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009)
ISSN1867-5662
ISBN978-3-642-01215-0
部门归属Su, Bai; Shen, Yidong Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100864, Peoples R China.
摘要To achieve good generalization in supervised learning, the training and testing examples are usually required to be drawn from the same source distribution. However, in many cases, this identical distribution assumption might be violated when a task from one new domain(target domain) comes, while there are only labeled data from a similar old domain (auxiliary domain). Labeling the new data can be costly and it would also be a waste to throw away all the old data. In this paper, we present a discriminative approach that utilizes the intrinsic geometry of input patterns revealed by unlabeled data points and derive a maximum-margin formulation of unsupervised transfer learning. Two alternative solutions are proposed to solve the problem. Experimental results on many real data sets demonstrate the effectiveness and the potential of the proposed methods.
主办者Huazhong Univ Sci & Technol, Chinese Univ Hong Kong, Natl Nat Sci Fdn China, IEEE Wuhan Sect, IEEE Computat Intelligence Soc, Int Neural Network Soc, Asia Pacific Neural Network Assembly, Euorpean Neural Network Soc, Hubei Province, Syst Engn Soc, IEEE Hong Kong Joint Chapter Robot & Automat & Control Syst
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/8322
专题基础软件与系统重点实验室
推荐引用方式
GB/T 7714
Su Bai,Xu Wei,Shen Yidong. margin-based transfer learning[C]. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY:SIXTH INTERNATIONAL SYMPOSIUM ON NEURAL NETWORKS (ISNN 2009),2009.
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